Impact Analytics Interview Questions and Answers for Experienced

Q1. Python questions, write a SQL query to return employee with the number of leaves in each month, Vlookup, Index Match, Rank, Dense Rank
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Q2. Loc and iloc in python
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loc and iloc are methods in pandas used for selecting rows and columns by label or integer position.
• loc is used for selecting rows and columns by label

• iloc is used for selecting rows and columns by integer position

• Example: df.loc[0:5, 'column_name']

• Example: df.iloc[0:5, 2]
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Q3. Advantage of Vlookup over-index match
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Vlookup is simpler and easier to use, while Index Match is more flexible and efficient.
• Vlookup is easier for beginners to understand and use

• Vlookup is quicker to set up and requires less formula writing

• Index Match is more flexible as it can look up values in any column, not just the first one

• Index Match is more efficient for large datasets as it does not require the entire column to be searched
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Q4. Difference between BRD and FRD
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BRD focuses on business requirements while FRD focuses on functional requirements.
• BRD (Business Requirements Document) outlines the business problem that needs to be solved.

• FRD (Functional Requirements Document) details how the system will meet the business requirements.

• BRD is more high-level and focuses on the 'what', while FRD is more detailed and focuses on the 'how'.

• BRD is typically created before FRD in the projec...read more
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Q5. Retail experience and analysis
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Retail experience and analysis
• I have over 5 years of experience in retail industry analysis

• Proficient in using data analytics tools to track sales trends and customer behavior

• Implemented strategies based on market research to increase sales and customer satisfaction

• Collaborated with cross-functional teams to optimize inventory management and pricing strategies
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Q1. Basic python question like sorting
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Q1. What are data structures in python,?
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Data structures in Python are ways to store and organize data efficiently.
• Data structures in Python include lists, tuples, dictionaries, sets, and arrays.

• Lists are ordered, mutable, and can contain duplicate elements.

• Tuples are ordered, immutable, and can contain duplicate elements.

• Dictionaries are unordered, mutable, and store data in key-value pairs.

• Sets are unordered, mutable, and do not allow duplicate elements.

• Arr...read more
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Q2. Sql join questions
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Started with sql questions then some basic python moved to machine learning concepts then one puzzle question (10 bags with a bag of defective coins identify in one step)

Q1. What are different types of regression analysis ?
Ans. 
Different types of regression analysis include linear regression, logistic regression, polynomial regression, ridge regression, and lasso regression.
• Linear regression: Predicts a continuous outcome based on one or more input features.

• Logistic regression: Predicts the probability of a binary outcome.

• Polynomial regression: Fits a curve to the data by including polynomial terms.

• Ridge regression: Adds a penalty term to the...read more
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Q2. What is confusion matrix?
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Confusion matrix is a table used to evaluate the performance of a classification model.
• It is a matrix with rows representing the actual class and columns representing the predicted class.

• It helps in visualizing the performance of a classification model by showing the counts of true positive, true negative, false positive, and false negative predictions.

• It is commonly used in machine learning to assess the quality of th...read more
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Q3. Questions around python programming
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Q1. Explain the architecture of Transformer based models.
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Transformer based models use self-attention mechanism to capture long-range dependencies in data.
• Transformer models consist of encoder and decoder layers.

• Self-attention mechanism allows each word to attend to all other words in the input sequence.

• Positional encoding is added to input embeddings to provide information about the position of words.

• Transformer models have achieved state-of-the-art results in various NLP ta...read more
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Q2. Different NLP techniques around extraction of text.
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Various NLP techniques for text extraction include Named Entity Recognition, Part-of-Speech tagging, and Dependency Parsing.
• Named Entity Recognition (NER) identifies entities such as names, dates, and locations in text.

• Part-of-Speech tagging assigns grammatical categories to words in a sentence.

• Dependency Parsing analyzes the grammatical structure of a sentence to identify relationships between words.
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